Half of all amalgam restorations fail within 10 years. Fractured margins is a primary cause for replacing between 10 and 33% of all the failed restorations and is a likely contributing factor to secondary caries, which accounts for 55% of all replacements. In order to understand marginal fracture and to subsequently minimize it, an understanding of the changes in microstructure that precede fracture is needed. The objective of this study is to identify the changes in microstructure that precede and lead to in vivo marginal fracture in high copper amalgam restorations. Amalgam restorations will be placed in denture teeth mounted in tooth-supported removable partial dentures. Patients receiving restorations will be recalled at 1,3,6,9,12,18 and 24 months. Clinical photographs and impressions of the restorations will be made at each recall. By comparing the marginal breakdown in the clinical photographs to that in a set of standard photographs, a marginal breakdown index will be obtained for each photograph. Replicas, which will reveal the internal microstructure of broken-down margins, will be made from the impressions. At each recall, sets of preselected teeth containing amalgam restorations will be removed from their partial denture. Fractured margins of the restorations will be examined at high magnification in an SEM and fracture mechanism will be determined. The progression of fracture at particular sites within the margin of a retrieved restoration will be followed by examining these sites in replicas of the restoration made at earlier recalls. The microstructure amalgam beneath broken-down margins will be analyzed. Areas within corrosion layers, near the cavosurface margins, beneath the occlusal surface, and midway down cavity walls will be analyzed separately. Corrosion products and amalgam phases will be identified using x-ray energy dispersive analysis and x-ray diffraction. Quantitative metallography will be used to measure grain sizes, shape indices and volume fractions of amalgam phases, corrosion products, and voids. For each retrieved restoration, there will be sets of microstructural data from each of the areas analyzed. These data sets, along with the marginal breakdown index of the restoration, will be used in a multiple regression analysis. By using data sets from many retrieved restorations, multiple regression analysis will determine the relative influence of the components of the microstructure on marginal breakdown.